dataProc

required packages: scde 3.0 (from bioconductor) CytobankAPI/tsne (for viSNE) cyt (for visualizing viSNE) ???? mclust 4.4 igraph 0.7.1 FactoMineR 1.28

#scde special install
if (!require("BiocManager", quietly = FALSE))
    install.packages("BiocManager")

Loading required package: BiocManager
Bioconductor version 3.14 (BiocManager 1.30.16), R 4.1.2 (2021-11-01)

Run this in terminal before attempting to install scde, because cairo is not pre-installed: sudo apt-get install libcairo2-dev

BiocManager::install("scde")

remotes packages can be used to install only mclust, igraph and FactoMineR.

#install packages using remotes (with specific version)
install.packages("remotes")  #get and install remotes first
library(remotes) #load remotes before everything else
#install_bioc("3.0/scde",upgrade="never") #installing from bioconductor github page
#install_version("scde","3.0") #not using the bioconductor install function
install_version("mclust","4.4")
install_version("igraph","0.7.1")
install_version("FactoMineR","1.28")

#install packages without using remotes (no specific version)
#install.packages("bioconductor") #??
#install.packages("scde") 
install.packages("CytobankAPI") #guaranteed and has ViSNE subpackage, but not sure if it's the one asked by paper (for ViSNE)

Installing package into ‘/home/jaic1/R/x86_64-pc-linux-gnu-library/4.1’
(as ‘lib’ is unspecified)
trying URL 'https://cloud.r-project.org/src/contrib/CytobankAPI_1.4.0.tar.gz'
Content type 'application/x-gzip' length 2510104 bytes (2.4 MB)
==================================================
downloaded 2.4 MB

* installing *source* package ‘CytobankAPI’ ...
** package ‘CytobankAPI’ successfully unpacked and MD5 sums checked
** using staged installation
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
*** copying figures
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (CytobankAPI)

The downloaded source packages are in
    ‘/tmp/RtmpojcNYW/downloaded_packages’

install.packages("tsne") #valid package, mentioned in paper but may not be right one because no subpackages (for ViSNE)

Installing package into ‘/home/jaic1/R/x86_64-pc-linux-gnu-library/4.1’
(as ‘lib’ is unspecified)
trying URL 'https://cloud.r-project.org/src/contrib/tsne_0.1-3.tar.gz'
Content type 'application/x-gzip' length 4553 bytes
==================================================
downloaded 4553 bytes

* installing *source* package ‘tsne’ ...
** package ‘tsne’ successfully unpacked and MD5 sums checked
** using staged installation
** R
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (tsne)

The downloaded source packages are in
    ‘/tmp/RtmpojcNYW/downloaded_packages’

install.packages("Rtsne")

Installing package into ‘/home/jaic1/R/x86_64-pc-linux-gnu-library/4.1’
(as ‘lib’ is unspecified)
trying URL 'https://cloud.r-project.org/src/contrib/Rtsne_0.15.tar.gz'
Content type 'application/x-gzip' length 67595 bytes (66 KB)
==================================================
downloaded 66 KB

* installing *source* package ‘Rtsne’ ...
** package ‘Rtsne’ successfully unpacked and MD5 sums checked
** using staged installation
** libs

g++ -std=gnu++14 -I"/usr/share/R/include" -DNDEBUG  -I'/home/jaic1/R/x86_64-pc-linux-gnu-library/4.1/Rcpp/include'   -fopenmp -fpic  -g -O2 -fdebug-prefix-map=/build/r-base-i2PIHO/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g  -c RcppExports.cpp -o RcppExports.o
g++ -std=gnu++14 -I"/usr/share/R/include" -DNDEBUG  -I'/home/jaic1/R/x86_64-pc-linux-gnu-library/4.1/Rcpp/include'   -fopenmp -fpic  -g -O2 -fdebug-prefix-map=/build/r-base-i2PIHO/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g  -c Rtsne.cpp -o Rtsne.o
g++ -std=gnu++14 -I"/usr/share/R/include" -DNDEBUG  -I'/home/jaic1/R/x86_64-pc-linux-gnu-library/4.1/Rcpp/include'   -fopenmp -fpic  -g -O2 -fdebug-prefix-map=/build/r-base-i2PIHO/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g  -c normalize_input.cpp -o normalize_input.o
g++ -std=gnu++14 -I"/usr/share/R/include" -DNDEBUG  -I'/home/jaic1/R/x86_64-pc-linux-gnu-library/4.1/Rcpp/include'   -fopenmp -fpic  -g -O2 -fdebug-prefix-map=/build/r-base-i2PIHO/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g  -c sptree.cpp -o sptree.o
g++ -std=gnu++14 -I"/usr/share/R/include" -DNDEBUG  -I'/home/jaic1/R/x86_64-pc-linux-gnu-library/4.1/Rcpp/include'   -fopenmp -fpic  -g -O2 -fdebug-prefix-map=/build/r-base-i2PIHO/r-base-4.1.2=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g  -c tsne.cpp -o tsne.o
g++ -std=gnu++14 -shared -L/usr/lib/R/lib -Wl,-Bsymbolic-functions -Wl,-z,relro -o Rtsne.so RcppExports.o Rtsne.o normalize_input.o sptree.o tsne.o -llapack -lblas -lgfortran -lm -lquadmath -fopenmp -L/usr/lib/R/lib -lR

installing to /home/jaic1/R/x86_64-pc-linux-gnu-library/4.1/00LOCK-Rtsne/00new/Rtsne/libs
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (Rtsne)

The downloaded source packages are in
    ‘/tmp/RtmpojcNYW/downloaded_packages’

#install.packages("mclust")
#install.packages("igraph")
#install.packages("FactoMineR")

#load packages
library(CytobankAPI)

Loading required package: curl
Using libcurl 7.68.0 with OpenSSL/1.1.1f
Loading required package: httr

Attaching package: ‘httr’

The following object is masked from ‘package:curl’:

    handle_reset

CytobankAPI 1.4.0
Type CytobankAPI_news() to see new features/changes/bug fixes.

Attaching package: ‘CytobankAPI’

The following object is masked from ‘package:httr’:

    authenticate

library(BiocManager)
library(scde)

Loading required package: flexmix
Loading required package: lattice

library(tsne)
library(Rtsne)
library(mclust)

Package 'mclust' version 4.4
Type 'citation("mclust")' for citing this R package in publications.

library(igraph)

Attaching package: ‘igraph’

The following object is masked from ‘package:flexmix’:

    clusters

library(FactoMineR)
library(tidyverse) #for tsne

Registered S3 methods overwritten by 'dbplyr':
  method         from
  print.tbl_lazy     
  print.tbl_sql      
── Attaching packages ────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.3.1 ──
✓ ggplot2 3.3.5     ✓ purrr   0.3.4
✓ tibble  3.1.6     ✓ dplyr   1.0.7
✓ tidyr   1.1.4     ✓ stringr 1.4.0
✓ readr   2.1.2     ✓ forcats 0.5.1
── Conflicts ───────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
x CytobankAPI::authenticate() masks httr::authenticate()
x tidyr::crossing()           masks igraph::crossing()
x dplyr::filter()             masks stats::filter()
x httr::handle_reset()        masks curl::handle_reset()
x dplyr::lag()                masks stats::lag()
x purrr::map()                masks mclust::map()
x readr::parse_date()         masks curl::parse_date()
x purrr::simplify()           masks igraph::simplify()

library(knitr) #for outputting and CytobankAPI

getwd()

[1] "/home/jaic1/Documents/srp/githubRepo/SRP/Pipeline1"

load data gse67835 GSE67835_RAW.tar from ncbi multiple csv file /home/jaic1/Documents/srp/gseCSV/GSM1657993_nochipID12.C23.csv file list: GSM1657871_1772078217.C03.csv GSM1657872_1772078217.C04.csv .. GSM1657990_1772078237.C84.csv GSM1657991_1772078237.C92.csv GSM1657992_nochipID12.C05.csv GSM1657993_nochipID12.C23.csv .. GSM1658365_nochipID4.C95.csv GSM1658366_nochipID4.C96.csv

#data <- read.csv(file.choose()) #if want to select file from pop-up window
data<-read.csv("../../../gseCSV/GSM1657871_1772078217.C03.csv", header = FALSE, stringsAsFactors = FALSE, sep = "\t") #use relative path
print(data)

find a way to put all csv into a single DF/matrix all input files starts with “GSM165”

#get all filenames starting with "GSM" (or "GSM165") using pattern matching and put into list
inputFileList<-list.files(path="../../../gseCSV",pattern="^GSM")#,full.names =)#,recursive = )

print(inputFileList)

  [1] "GSM1657871_1772078217.C03.csv" "GSM1657872_1772078217.C04.csv" "GSM1657873_1772078217.C06.csv" "GSM1657874_1772078217.C07.csv"
  [5] "GSM1657875_1772078217.C08.csv" "GSM1657876_1772078217.C09.csv" "GSM1657877_1772078217.C14.csv" "GSM1657878_1772078217.C16.csv"
  [9] "GSM1657879_1772078217.C17.csv" "GSM1657880_1772078217.C18.csv" "GSM1657881_1772078217.C20.csv" "GSM1657882_1772078217.C23.csv"
 [13] "GSM1657883_1772078217.C28.csv" "GSM1657884_1772078217.C29.csv" "GSM1657885_1772078217.C32.csv" "GSM1657886_1772078217.C33.csv"
 [17] "GSM1657887_1772078217.C39.csv" "GSM1657888_1772078217.C40.csv" "GSM1657889_1772078217.C47.csv" "GSM1657890_1772078217.C52.csv"
 [21] "GSM1657891_1772078217.C56.csv" "GSM1657892_1772078217.C58.csv" "GSM1657893_1772078217.C59.csv" "GSM1657894_1772078217.C60.csv"
 [25] "GSM1657895_1772078217.C61.csv" "GSM1657896_1772078217.C66.csv" "GSM1657897_1772078217.C72.csv" "GSM1657898_1772078217.C80.csv"
 [29] "GSM1657899_1772078217.C87.csv" "GSM1657900_1772078217.C89.csv" "GSM1657901_1772078217.C91.csv" "GSM1657902_1772078217.C94.csv"
 [33] "GSM1657903_1772078217.C96.csv" "GSM1657904_1772078218.C05.csv" "GSM1657905_1772078218.C08.csv" "GSM1657906_1772078218.C09.csv"
 [37] "GSM1657907_1772078218.C13.csv" "GSM1657908_1772078218.C18.csv" "GSM1657909_1772078218.C23.csv" "GSM1657910_1772078218.C27.csv"
 [41] "GSM1657911_1772078218.C29.csv" "GSM1657912_1772078218.C32.csv" "GSM1657913_1772078218.C34.csv" "GSM1657914_1772078218.C43.csv"
 [45] "GSM1657915_1772078218.C44.csv" "GSM1657916_1772078218.C47.csv" "GSM1657917_1772078218.C48.csv" "GSM1657918_1772078218.C53.csv"
 [49] "GSM1657919_1772078218.C55.csv" "GSM1657920_1772078218.C56.csv" "GSM1657921_1772078218.C58.csv" "GSM1657922_1772078218.C61.csv"
 [53] "GSM1657923_1772078218.C71.csv" "GSM1657924_1772078218.C85.csv" "GSM1657925_1772078218.C88.csv" "GSM1657926_1772078218.C89.csv"
 [57] "GSM1657927_1772078218.C93.csv" "GSM1657928_1772078218.C95.csv" "GSM1657929_1772078236.C11.csv" "GSM1657930_1772078236.C12.csv"
 [61] "GSM1657931_1772078236.C16.csv" "GSM1657932_1772078236.C17.csv" "GSM1657933_1772078236.C19.csv" "GSM1657934_1772078236.C25.csv"
 [65] "GSM1657935_1772078236.C26.csv" "GSM1657936_1772078236.C27.csv" "GSM1657937_1772078236.C28.csv" "GSM1657938_1772078236.C30.csv"
 [69] "GSM1657939_1772078236.C31.csv" "GSM1657940_1772078236.C32.csv" "GSM1657941_1772078236.C33.csv" "GSM1657942_1772078236.C34.csv"
 [73] "GSM1657943_1772078236.C36.csv" "GSM1657944_1772078236.C38.csv" "GSM1657945_1772078236.C40.csv" "GSM1657946_1772078236.C41.csv"
 [77] "GSM1657947_1772078236.C45.csv" "GSM1657948_1772078236.C46.csv" "GSM1657949_1772078236.C47.csv" "GSM1657950_1772078236.C49.csv"
 [81] "GSM1657951_1772078236.C54.csv" "GSM1657952_1772078236.C56.csv" "GSM1657953_1772078236.C57.csv" "GSM1657954_1772078236.C61.csv"
 [85] "GSM1657955_1772078236.C65.csv" "GSM1657956_1772078236.C66.csv" "GSM1657957_1772078236.C70.csv" "GSM1657958_1772078236.C74.csv"
 [89] "GSM1657959_1772078236.C77.csv" "GSM1657960_1772078236.C89.csv" "GSM1657961_1772078236.C90.csv" "GSM1657962_1772078236.C93.csv"
 [93] "GSM1657963_1772078237.C06.csv" "GSM1657964_1772078237.C08.csv" "GSM1657965_1772078237.C11.csv" "GSM1657966_1772078237.C13.csv"
 [97] "GSM1657967_1772078237.C14.csv" "GSM1657968_1772078237.C15.csv" "GSM1657969_1772078237.C19.csv" "GSM1657970_1772078237.C21.csv"
[101] "GSM1657971_1772078237.C26.csv" "GSM1657972_1772078237.C28.csv" "GSM1657973_1772078237.C29.csv" "GSM1657974_1772078237.C31.csv"
[105] "GSM1657975_1772078237.C40.csv" "GSM1657976_1772078237.C42.csv" "GSM1657977_1772078237.C44.csv" "GSM1657978_1772078237.C47.csv"
[109] "GSM1657979_1772078237.C49.csv" "GSM1657980_1772078237.C52.csv" "GSM1657981_1772078237.C55.csv" "GSM1657982_1772078237.C56.csv"
[113] "GSM1657983_1772078237.C58.csv" "GSM1657984_1772078237.C60.csv" "GSM1657985_1772078237.C61.csv" "GSM1657986_1772078237.C62.csv"
[117] "GSM1657987_1772078237.C74.csv" "GSM1657988_1772078237.C79.csv" "GSM1657989_1772078237.C83.csv" "GSM1657990_1772078237.C84.csv"
[121] "GSM1657991_1772078237.C92.csv" "GSM1657992_nochipID12.C05.csv" "GSM1657993_nochipID12.C23.csv" "GSM1657994_nochipID12.C73.csv"
[125] "GSM1657995_nochipID12.C84.csv" "GSM1657996_nochipID12.C87.csv" "GSM1657997_nochipID14.C08.csv" "GSM1657998_nochipID14.C13.csv"
[129] "GSM1657999_nochipID14.C29.csv" "GSM1658000_nochipID14.C45.csv" "GSM1658001_nochipID14.C89.csv" "GSM1658002_nochipID15.C20.csv"
[133] "GSM1658003_nochipID15.C54.csv" "GSM1658004_nochipID15.C69.csv" "GSM1658005_nochipID15.C86.csv" "GSM1658006_nochipID2.C01.csv" 
[137] "GSM1658007_nochipID2.C02.csv"  "GSM1658008_nochipID2.C03.csv"  "GSM1658009_nochipID2.C07.csv"  "GSM1658010_nochipID2.C08.csv" 
[141] "GSM1658011_nochipID2.C09.csv"  "GSM1658012_nochipID2.C10.csv"  "GSM1658013_nochipID2.C11.csv"  "GSM1658014_nochipID2.C12.csv" 
[145] "GSM1658015_nochipID2.C13.csv"  "GSM1658016_nochipID2.C14.csv"  "GSM1658017_nochipID2.C15.csv"  "GSM1658018_nochipID2.C16.csv" 
[149] "GSM1658019_nochipID2.C17.csv"  "GSM1658020_nochipID2.C18.csv"  "GSM1658021_nochipID2.C19.csv"  "GSM1658022_nochipID2.C21.csv" 
[153] "GSM1658023_nochipID2.C22.csv"  "GSM1658024_nochipID2.C24.csv"  "GSM1658025_nochipID2.C26.csv"  "GSM1658026_nochipID2.C27.csv" 
[157] "GSM1658027_nochipID2.C28.csv"  "GSM1658028_nochipID2.C29.csv"  "GSM1658029_nochipID2.C30.csv"  "GSM1658030_nochipID2.C31.csv" 
[161] "GSM1658031_nochipID2.C32.csv"  "GSM1658032_nochipID2.C33.csv"  "GSM1658033_nochipID2.C34.csv"  "GSM1658034_nochipID2.C36.csv" 
[165] "GSM1658035_nochipID2.C38.csv"  "GSM1658036_nochipID2.C39.csv"  "GSM1658037_nochipID2.C40.csv"  "GSM1658038_nochipID2.C41.csv" 
[169] "GSM1658039_nochipID2.C42.csv"  "GSM1658040_nochipID2.C43.csv"  "GSM1658041_nochipID2.C44.csv"  "GSM1658042_nochipID2.C45.csv" 
[173] "GSM1658043_nochipID2.C46.csv"  "GSM1658044_nochipID2.C47.csv"  "GSM1658045_nochipID2.C48.csv"  "GSM1658046_nochipID2.C49.csv" 
[177] "GSM1658047_nochipID2.C50.csv"  "GSM1658048_nochipID2.C51.csv"  "GSM1658049_nochipID2.C52.csv"  "GSM1658050_nochipID2.C56.csv" 
[181] "GSM1658051_nochipID2.C57.csv"  "GSM1658052_nochipID2.C58.csv"  "GSM1658053_nochipID2.C59.csv"  "GSM1658054_nochipID2.C60.csv" 
[185] "GSM1658055_nochipID2.C61.csv"  "GSM1658056_nochipID2.C62.csv"  "GSM1658057_nochipID2.C63.csv"  "GSM1658058_nochipID2.C64.csv" 
[189] "GSM1658059_nochipID2.C65.csv"  "GSM1658060_nochipID2.C66.csv"  "GSM1658061_nochipID2.C67.csv"  "GSM1658062_nochipID2.C68.csv" 
[193] "GSM1658063_nochipID2.C69.csv"  "GSM1658064_nochipID2.C71.csv"  "GSM1658065_nochipID2.C73.csv"  "GSM1658066_nochipID2.C75.csv" 
[197] "GSM1658067_nochipID2.C76.csv"  "GSM1658068_nochipID2.C77.csv"  "GSM1658069_nochipID2.C78.csv"  "GSM1658070_nochipID2.C79.csv" 
[201] "GSM1658071_nochipID2.C80.csv"  "GSM1658072_nochipID2.C81.csv"  "GSM1658073_nochipID2.C82.csv"  "GSM1658074_nochipID2.C83.csv" 
[205] "GSM1658075_nochipID2.C84.csv"  "GSM1658076_nochipID2.C85.csv"  "GSM1658077_nochipID2.C86.csv"  "GSM1658078_nochipID2.C87.csv" 
[209] "GSM1658079_nochipID2.C89.csv"  "GSM1658080_nochipID2.C90.csv"  "GSM1658081_nochipID2.C92.csv"  "GSM1658082_nochipID2.C93.csv" 
[213] "GSM1658083_nochipID3.C01.csv"  "GSM1658084_nochipID3.C05.csv"  "GSM1658085_nochipID3.C06.csv"  "GSM1658086_nochipID3.C07.csv" 
[217] "GSM1658087_nochipID3.C09.csv"  "GSM1658088_nochipID3.C11.csv"  "GSM1658089_nochipID3.C12.csv"  "GSM1658090_nochipID3.C14.csv" 
[221] "GSM1658091_nochipID3.C23.csv"  "GSM1658092_nochipID3.C25.csv"  "GSM1658093_nochipID3.C32.csv"  "GSM1658094_nochipID3.C37.csv" 
[225] "GSM1658095_nochipID3.C38.csv"  "GSM1658096_nochipID3.C51.csv"  "GSM1658097_nochipID3.C52.csv"  "GSM1658098_nochipID3.C53.csv" 
[229] "GSM1658099_nochipID3.C54.csv"  "GSM1658100_nochipID3.C56.csv"  "GSM1658101_nochipID3.C61.csv"  "GSM1658102_nochipID3.C62.csv" 
[233] "GSM1658103_nochipID3.C65.csv"  "GSM1658104_nochipID3.C69.csv"  "GSM1658105_nochipID3.C71.csv"  "GSM1658106_nochipID3.C72.csv" 
[237] "GSM1658107_nochipID3.C74.csv"  "GSM1658108_nochipID3.C75.csv"  "GSM1658109_nochipID3.C76.csv"  "GSM1658110_nochipID3.C80.csv" 
[241] "GSM1658111_nochipID3.C81.csv"  "GSM1658112_nochipID3.C84.csv"  "GSM1658113_nochipID3.C85.csv"  "GSM1658114_nochipID3.C86.csv" 
[245] "GSM1658115_nochipID3.C91.csv"  "GSM1658116_nochipID5.C04.csv"  "GSM1658117_nochipID5.C05.csv"  "GSM1658118_nochipID5.C18.csv" 
[249] "GSM1658119_nochipID5.C19.csv"  "GSM1658120_nochipID5.C42.csv"  "GSM1658121_nochipID5.C44.csv"  "GSM1658122_nochipID5.C45.csv" 
[253] "GSM1658123_nochipID5.C54.csv"  "GSM1658124_nochipID5.C65.csv"  "GSM1658125_nochipID5.C72.csv"  "GSM1658126_nochipID5.C91.csv" 
[257] "GSM1658127_nochipID8.C01.csv"  "GSM1658128_nochipID8.C02.csv"  "GSM1658129_nochipID8.C05.csv"  "GSM1658130_nochipID8.C06.csv" 
[261] "GSM1658131_nochipID8.C08.csv"  "GSM1658132_nochipID8.C11.csv"  "GSM1658133_nochipID8.C12.csv"  "GSM1658134_nochipID8.C13.csv" 
[265] "GSM1658135_nochipID8.C14.csv"  "GSM1658136_nochipID8.C17.csv"  "GSM1658137_nochipID8.C19.csv"  "GSM1658138_nochipID8.C20.csv" 
[269] "GSM1658139_nochipID8.C22.csv"  "GSM1658140_nochipID8.C23.csv"  "GSM1658141_nochipID8.C25.csv"  "GSM1658142_nochipID8.C28.csv" 
[273] "GSM1658143_nochipID8.C29.csv"  "GSM1658144_nochipID8.C30.csv"  "GSM1658145_nochipID8.C32.csv"  "GSM1658146_nochipID8.C36.csv" 
[277] "GSM1658147_nochipID8.C37.csv"  "GSM1658148_nochipID8.C39.csv"  "GSM1658149_nochipID8.C40.csv"  "GSM1658150_nochipID8.C41.csv" 
[281] "GSM1658151_nochipID8.C42.csv"  "GSM1658152_nochipID8.C43.csv"  "GSM1658153_nochipID8.C45.csv"  "GSM1658154_nochipID8.C48.csv" 
[285] "GSM1658155_nochipID8.C49.csv"  "GSM1658156_nochipID8.C50.csv"  "GSM1658157_nochipID8.C52.csv"  "GSM1658158_nochipID8.C53.csv" 
[289] "GSM1658159_nochipID8.C54.csv"  "GSM1658160_nochipID8.C55.csv"  "GSM1658161_nochipID8.C56.csv"  "GSM1658162_nochipID8.C57.csv" 
[293] "GSM1658163_nochipID8.C60.csv"  "GSM1658164_nochipID8.C61.csv"  "GSM1658165_nochipID8.C64.csv"  "GSM1658166_nochipID8.C65.csv" 
[297] "GSM1658167_nochipID8.C66.csv"  "GSM1658168_nochipID8.C67.csv"  "GSM1658169_nochipID8.C70.csv"  "GSM1658170_nochipID8.C75.csv" 
[301] "GSM1658171_nochipID8.C77.csv"  "GSM1658172_nochipID8.C78.csv"  "GSM1658173_nochipID8.C79.csv"  "GSM1658174_nochipID8.C81.csv" 
[305] "GSM1658175_nochipID8.C82.csv"  "GSM1658176_nochipID8.C84.csv"  "GSM1658177_nochipID8.C85.csv"  "GSM1658178_nochipID8.C87.csv" 
[309] "GSM1658179_nochipID8.C88.csv"  "GSM1658180_nochipID8.C90.csv"  "GSM1658181_nochipID8.C92.csv"  "GSM1658182_nochipID8.C95.csv" 
[313] "GSM1658183_nochipID8.C96.csv"  "GSM1658184_nochipID9.C01.csv"  "GSM1658185_nochipID9.C02.csv"  "GSM1658186_nochipID9.C04.csv" 
[317] "GSM1658187_nochipID9.C09.csv"  "GSM1658188_nochipID9.C14.csv"  "GSM1658189_nochipID9.C18.csv"  "GSM1658190_nochipID9.C26.csv" 
[321] "GSM1658191_nochipID9.C37.csv"  "GSM1658192_nochipID9.C42.csv"  "GSM1658193_nochipID9.C57.csv"  "GSM1658194_nochipID9.C59.csv" 
[325] "GSM1658195_nochipID9.C62.csv"  "GSM1658196_nochipID9.C65.csv"  "GSM1658197_nochipID9.C74.csv"  "GSM1658198_nochipID9.C75.csv" 
[329] "GSM1658199_nochipID9.C84.csv"  "GSM1658200_nochipID9.C85.csv"  "GSM1658201_nochipID9.C87.csv"  "GSM1658202_nochipID9.C92.csv" 
[333] "GSM1658203_nochipID10.C02.csv" "GSM1658204_nochipID10.C03.csv" "GSM1658205_nochipID10.C05.csv" "GSM1658206_nochipID10.C07.csv"
[337] "GSM1658207_nochipID10.C11.csv" "GSM1658208_nochipID10.C16.csv" "GSM1658209_nochipID10.C17.csv" "GSM1658210_nochipID10.C19.csv"
[341] "GSM1658211_nochipID10.C25.csv" "GSM1658212_nochipID10.C26.csv" "GSM1658213_nochipID10.C37.csv" "GSM1658214_nochipID10.C39.csv"
[345] "GSM1658215_nochipID10.C42.csv" "GSM1658216_nochipID10.C44.csv" "GSM1658217_nochipID10.C47.csv" "GSM1658218_nochipID10.C49.csv"
[349] "GSM1658219_nochipID10.C50.csv" "GSM1658220_nochipID10.C53.csv" "GSM1658221_nochipID10.C58.csv" "GSM1658222_nochipID10.C65.csv"
[353] "GSM1658223_nochipID10.C74.csv" "GSM1658224_nochipID10.C75.csv" "GSM1658225_nochipID10.C85.csv" "GSM1658226_nochipID10.C88.csv"
[357] "GSM1658227_nochipID10.C93.csv" "GSM1658228_nochipID10.C94.csv" "GSM1658229_nochipID11.C02.csv" "GSM1658230_nochipID11.C03.csv"
[361] "GSM1658231_nochipID11.C06.csv" "GSM1658232_nochipID11.C07.csv" "GSM1658233_nochipID11.C08.csv" "GSM1658234_nochipID11.C10.csv"
[365] "GSM1658235_nochipID11.C15.csv" "GSM1658236_nochipID11.C17.csv" "GSM1658237_nochipID11.C19.csv" "GSM1658238_nochipID11.C20.csv"
[369] "GSM1658239_nochipID11.C21.csv" "GSM1658240_nochipID11.C22.csv" "GSM1658241_nochipID11.C23.csv" "GSM1658242_nochipID11.C25.csv"
[373] "GSM1658243_nochipID11.C30.csv" "GSM1658244_nochipID11.C37.csv" "GSM1658245_nochipID11.C48.csv" "GSM1658246_nochipID11.C49.csv"
[377] "GSM1658247_nochipID11.C50.csv" "GSM1658248_nochipID11.C53.csv" "GSM1658249_nochipID11.C54.csv" "GSM1658251_nochipID11.C55.csv"
[381] "GSM1658253_nochipID11.C56.csv" "GSM1658255_nochipID11.C57.csv" "GSM1658257_nochipID11.C58.csv" "GSM1658259_nochipID11.C59.csv"
[385] "GSM1658262_nochipID11.C60.csv" "GSM1658264_nochipID11.C61.csv" "GSM1658266_nochipID11.C62.csv" "GSM1658268_nochipID11.C63.csv"
[389] "GSM1658270_nochipID11.C64.csv" "GSM1658272_nochipID11.C66.csv" "GSM1658275_nochipID11.C68.csv" "GSM1658277_nochipID11.C69.csv"
[393] "GSM1658279_nochipID11.C75.csv" "GSM1658281_nochipID11.C76.csv" "GSM1658284_nochipID11.C77.csv" "GSM1658286_nochipID11.C78.csv"
[397] "GSM1658288_nochipID11.C79.csv" "GSM1658290_nochipID11.C81.csv" "GSM1658292_nochipID11.C82.csv" "GSM1658294_nochipID11.C83.csv"
[401] "GSM1658297_nochipID11.C84.csv" "GSM1658299_nochipID11.C86.csv" "GSM1658301_nochipID11.C91.csv" "GSM1658304_nochipID11.C93.csv"
[405] "GSM1658305_nochipID13.C07.csv" "GSM1658306_nochipID13.C11.csv" "GSM1658307_nochipID13.C12.csv" "GSM1658308_nochipID13.C14.csv"
[409] "GSM1658309_nochipID13.C15.csv" "GSM1658310_nochipID13.C17.csv" "GSM1658311_nochipID13.C21.csv" "GSM1658312_nochipID13.C25.csv"
[413] "GSM1658313_nochipID13.C28.csv" "GSM1658314_nochipID13.C32.csv" "GSM1658315_nochipID13.C36.csv" "GSM1658316_nochipID13.C45.csv"
[417] "GSM1658317_nochipID13.C46.csv" "GSM1658318_nochipID13.C48.csv" "GSM1658319_nochipID13.C50.csv" "GSM1658320_nochipID13.C55.csv"
[421] "GSM1658321_nochipID13.C57.csv" "GSM1658322_nochipID13.C58.csv" "GSM1658323_nochipID13.C59.csv" "GSM1658324_nochipID13.C61.csv"
[425] "GSM1658325_nochipID13.C63.csv" "GSM1658326_nochipID13.C64.csv" "GSM1658327_nochipID13.C66.csv" "GSM1658328_nochipID13.C67.csv"
[429] "GSM1658329_nochipID13.C68.csv" "GSM1658330_nochipID13.C72.csv" "GSM1658331_nochipID13.C73.csv" "GSM1658332_nochipID13.C74.csv"
[433] "GSM1658333_nochipID13.C75.csv" "GSM1658334_nochipID13.C80.csv" "GSM1658335_nochipID13.C84.csv" "GSM1658336_nochipID13.C87.csv"
[437] "GSM1658337_nochipID13.C93.csv" "GSM1658338_nochipID4.C03.csv"  "GSM1658339_nochipID4.C04.csv"  "GSM1658340_nochipID4.C10.csv" 
[441] "GSM1658341_nochipID4.C14.csv"  "GSM1658342_nochipID4.C18.csv"  "GSM1658343_nochipID4.C19.csv"  "GSM1658344_nochipID4.C20.csv" 
[445] "GSM1658345_nochipID4.C21.csv"  "GSM1658346_nochipID4.C33.csv"  "GSM1658347_nochipID4.C34.csv"  "GSM1658348_nochipID4.C38.csv" 
[449] "GSM1658349_nochipID4.C39.csv"  "GSM1658350_nochipID4.C41.csv"  "GSM1658351_nochipID4.C42.csv"  "GSM1658352_nochipID4.C44.csv" 
[453] "GSM1658353_nochipID4.C49.csv"  "GSM1658354_nochipID4.C52.csv"  "GSM1658355_nochipID4.C53.csv"  "GSM1658356_nochipID4.C59.csv" 
[457] "GSM1658357_nochipID4.C62.csv"  "GSM1658358_nochipID4.C63.csv"  "GSM1658359_nochipID4.C66.csv"  "GSM1658360_nochipID4.C74.csv" 
[461] "GSM1658361_nochipID4.C77.csv"  "GSM1658362_nochipID4.C78.csv"  "GSM1658363_nochipID4.C84.csv"  "GSM1658364_nochipID4.C89.csv" 
[465] "GSM1658365_nochipID4.C95.csv"  "GSM1658366_nochipID4.C96.csv" 

test<-inputFileList
test<-sub(".csv$", "", test)
print(test)

  [1] "GSM1657871_1772078217.C03" "GSM1657872_1772078217.C04" "GSM1657873_1772078217.C06" "GSM1657874_1772078217.C07"
  [5] "GSM1657875_1772078217.C08" "GSM1657876_1772078217.C09" "GSM1657877_1772078217.C14" "GSM1657878_1772078217.C16"
  [9] "GSM1657879_1772078217.C17" "GSM1657880_1772078217.C18" "GSM1657881_1772078217.C20" "GSM1657882_1772078217.C23"
 [13] "GSM1657883_1772078217.C28" "GSM1657884_1772078217.C29" "GSM1657885_1772078217.C32" "GSM1657886_1772078217.C33"
 [17] "GSM1657887_1772078217.C39" "GSM1657888_1772078217.C40" "GSM1657889_1772078217.C47" "GSM1657890_1772078217.C52"
 [21] "GSM1657891_1772078217.C56" "GSM1657892_1772078217.C58" "GSM1657893_1772078217.C59" "GSM1657894_1772078217.C60"
 [25] "GSM1657895_1772078217.C61" "GSM1657896_1772078217.C66" "GSM1657897_1772078217.C72" "GSM1657898_1772078217.C80"
 [29] "GSM1657899_1772078217.C87" "GSM1657900_1772078217.C89" "GSM1657901_1772078217.C91" "GSM1657902_1772078217.C94"
 [33] "GSM1657903_1772078217.C96" "GSM1657904_1772078218.C05" "GSM1657905_1772078218.C08" "GSM1657906_1772078218.C09"
 [37] "GSM1657907_1772078218.C13" "GSM1657908_1772078218.C18" "GSM1657909_1772078218.C23" "GSM1657910_1772078218.C27"
 [41] "GSM1657911_1772078218.C29" "GSM1657912_1772078218.C32" "GSM1657913_1772078218.C34" "GSM1657914_1772078218.C43"
 [45] "GSM1657915_1772078218.C44" "GSM1657916_1772078218.C47" "GSM1657917_1772078218.C48" "GSM1657918_1772078218.C53"
 [49] "GSM1657919_1772078218.C55" "GSM1657920_1772078218.C56" "GSM1657921_1772078218.C58" "GSM1657922_1772078218.C61"
 [53] "GSM1657923_1772078218.C71" "GSM1657924_1772078218.C85" "GSM1657925_1772078218.C88" "GSM1657926_1772078218.C89"
 [57] "GSM1657927_1772078218.C93" "GSM1657928_1772078218.C95" "GSM1657929_1772078236.C11" "GSM1657930_1772078236.C12"
 [61] "GSM1657931_1772078236.C16" "GSM1657932_1772078236.C17" "GSM1657933_1772078236.C19" "GSM1657934_1772078236.C25"
 [65] "GSM1657935_1772078236.C26" "GSM1657936_1772078236.C27" "GSM1657937_1772078236.C28" "GSM1657938_1772078236.C30"
 [69] "GSM1657939_1772078236.C31" "GSM1657940_1772078236.C32" "GSM1657941_1772078236.C33" "GSM1657942_1772078236.C34"
 [73] "GSM1657943_1772078236.C36" "GSM1657944_1772078236.C38" "GSM1657945_1772078236.C40" "GSM1657946_1772078236.C41"
 [77] "GSM1657947_1772078236.C45" "GSM1657948_1772078236.C46" "GSM1657949_1772078236.C47" "GSM1657950_1772078236.C49"
 [81] "GSM1657951_1772078236.C54" "GSM1657952_1772078236.C56" "GSM1657953_1772078236.C57" "GSM1657954_1772078236.C61"
 [85] "GSM1657955_1772078236.C65" "GSM1657956_1772078236.C66" "GSM1657957_1772078236.C70" "GSM1657958_1772078236.C74"
 [89] "GSM1657959_1772078236.C77" "GSM1657960_1772078236.C89" "GSM1657961_1772078236.C90" "GSM1657962_1772078236.C93"
 [93] "GSM1657963_1772078237.C06" "GSM1657964_1772078237.C08" "GSM1657965_1772078237.C11" "GSM1657966_1772078237.C13"
 [97] "GSM1657967_1772078237.C14" "GSM1657968_1772078237.C15" "GSM1657969_1772078237.C19" "GSM1657970_1772078237.C21"
[101] "GSM1657971_1772078237.C26" "GSM1657972_1772078237.C28" "GSM1657973_1772078237.C29" "GSM1657974_1772078237.C31"
[105] "GSM1657975_1772078237.C40" "GSM1657976_1772078237.C42" "GSM1657977_1772078237.C44" "GSM1657978_1772078237.C47"
[109] "GSM1657979_1772078237.C49" "GSM1657980_1772078237.C52" "GSM1657981_1772078237.C55" "GSM1657982_1772078237.C56"
[113] "GSM1657983_1772078237.C58" "GSM1657984_1772078237.C60" "GSM1657985_1772078237.C61" "GSM1657986_1772078237.C62"
[117] "GSM1657987_1772078237.C74" "GSM1657988_1772078237.C79" "GSM1657989_1772078237.C83" "GSM1657990_1772078237.C84"
[121] "GSM1657991_1772078237.C92" "GSM1657992_nochipID12.C05" "GSM1657993_nochipID12.C23" "GSM1657994_nochipID12.C73"
[125] "GSM1657995_nochipID12.C84" "GSM1657996_nochipID12.C87" "GSM1657997_nochipID14.C08" "GSM1657998_nochipID14.C13"
[129] "GSM1657999_nochipID14.C29" "GSM1658000_nochipID14.C45" "GSM1658001_nochipID14.C89" "GSM1658002_nochipID15.C20"
[133] "GSM1658003_nochipID15.C54" "GSM1658004_nochipID15.C69" "GSM1658005_nochipID15.C86" "GSM1658006_nochipID2.C01" 
[137] "GSM1658007_nochipID2.C02"  "GSM1658008_nochipID2.C03"  "GSM1658009_nochipID2.C07"  "GSM1658010_nochipID2.C08" 
[141] "GSM1658011_nochipID2.C09"  "GSM1658012_nochipID2.C10"  "GSM1658013_nochipID2.C11"  "GSM1658014_nochipID2.C12" 
[145] "GSM1658015_nochipID2.C13"  "GSM1658016_nochipID2.C14"  "GSM1658017_nochipID2.C15"  "GSM1658018_nochipID2.C16" 
[149] "GSM1658019_nochipID2.C17"  "GSM1658020_nochipID2.C18"  "GSM1658021_nochipID2.C19"  "GSM1658022_nochipID2.C21" 
[153] "GSM1658023_nochipID2.C22"  "GSM1658024_nochipID2.C24"  "GSM1658025_nochipID2.C26"  "GSM1658026_nochipID2.C27" 
[157] "GSM1658027_nochipID2.C28"  "GSM1658028_nochipID2.C29"  "GSM1658029_nochipID2.C30"  "GSM1658030_nochipID2.C31" 
[161] "GSM1658031_nochipID2.C32"  "GSM1658032_nochipID2.C33"  "GSM1658033_nochipID2.C34"  "GSM1658034_nochipID2.C36" 
[165] "GSM1658035_nochipID2.C38"  "GSM1658036_nochipID2.C39"  "GSM1658037_nochipID2.C40"  "GSM1658038_nochipID2.C41" 
[169] "GSM1658039_nochipID2.C42"  "GSM1658040_nochipID2.C43"  "GSM1658041_nochipID2.C44"  "GSM1658042_nochipID2.C45" 
[173] "GSM1658043_nochipID2.C46"  "GSM1658044_nochipID2.C47"  "GSM1658045_nochipID2.C48"  "GSM1658046_nochipID2.C49" 
[177] "GSM1658047_nochipID2.C50"  "GSM1658048_nochipID2.C51"  "GSM1658049_nochipID2.C52"  "GSM1658050_nochipID2.C56" 
[181] "GSM1658051_nochipID2.C57"  "GSM1658052_nochipID2.C58"  "GSM1658053_nochipID2.C59"  "GSM1658054_nochipID2.C60" 
[185] "GSM1658055_nochipID2.C61"  "GSM1658056_nochipID2.C62"  "GSM1658057_nochipID2.C63"  "GSM1658058_nochipID2.C64" 
[189] "GSM1658059_nochipID2.C65"  "GSM1658060_nochipID2.C66"  "GSM1658061_nochipID2.C67"  "GSM1658062_nochipID2.C68" 
[193] "GSM1658063_nochipID2.C69"  "GSM1658064_nochipID2.C71"  "GSM1658065_nochipID2.C73"  "GSM1658066_nochipID2.C75" 
[197] "GSM1658067_nochipID2.C76"  "GSM1658068_nochipID2.C77"  "GSM1658069_nochipID2.C78"  "GSM1658070_nochipID2.C79" 
[201] "GSM1658071_nochipID2.C80"  "GSM1658072_nochipID2.C81"  "GSM1658073_nochipID2.C82"  "GSM1658074_nochipID2.C83" 
[205] "GSM1658075_nochipID2.C84"  "GSM1658076_nochipID2.C85"  "GSM1658077_nochipID2.C86"  "GSM1658078_nochipID2.C87" 
[209] "GSM1658079_nochipID2.C89"  "GSM1658080_nochipID2.C90"  "GSM1658081_nochipID2.C92"  "GSM1658082_nochipID2.C93" 
[213] "GSM1658083_nochipID3.C01"  "GSM1658084_nochipID3.C05"  "GSM1658085_nochipID3.C06"  "GSM1658086_nochipID3.C07" 
[217] "GSM1658087_nochipID3.C09"  "GSM1658088_nochipID3.C11"  "GSM1658089_nochipID3.C12"  "GSM1658090_nochipID3.C14" 
[221] "GSM1658091_nochipID3.C23"  "GSM1658092_nochipID3.C25"  "GSM1658093_nochipID3.C32"  "GSM1658094_nochipID3.C37" 
[225] "GSM1658095_nochipID3.C38"  "GSM1658096_nochipID3.C51"  "GSM1658097_nochipID3.C52"  "GSM1658098_nochipID3.C53" 
[229] "GSM1658099_nochipID3.C54"  "GSM1658100_nochipID3.C56"  "GSM1658101_nochipID3.C61"  "GSM1658102_nochipID3.C62" 
[233] "GSM1658103_nochipID3.C65"  "GSM1658104_nochipID3.C69"  "GSM1658105_nochipID3.C71"  "GSM1658106_nochipID3.C72" 
[237] "GSM1658107_nochipID3.C74"  "GSM1658108_nochipID3.C75"  "GSM1658109_nochipID3.C76"  "GSM1658110_nochipID3.C80" 
[241] "GSM1658111_nochipID3.C81"  "GSM1658112_nochipID3.C84"  "GSM1658113_nochipID3.C85"  "GSM1658114_nochipID3.C86" 
[245] "GSM1658115_nochipID3.C91"  "GSM1658116_nochipID5.C04"  "GSM1658117_nochipID5.C05"  "GSM1658118_nochipID5.C18" 
[249] "GSM1658119_nochipID5.C19"  "GSM1658120_nochipID5.C42"  "GSM1658121_nochipID5.C44"  "GSM1658122_nochipID5.C45" 
[253] "GSM1658123_nochipID5.C54"  "GSM1658124_nochipID5.C65"  "GSM1658125_nochipID5.C72"  "GSM1658126_nochipID5.C91" 
[257] "GSM1658127_nochipID8.C01"  "GSM1658128_nochipID8.C02"  "GSM1658129_nochipID8.C05"  "GSM1658130_nochipID8.C06" 
[261] "GSM1658131_nochipID8.C08"  "GSM1658132_nochipID8.C11"  "GSM1658133_nochipID8.C12"  "GSM1658134_nochipID8.C13" 
[265] "GSM1658135_nochipID8.C14"  "GSM1658136_nochipID8.C17"  "GSM1658137_nochipID8.C19"  "GSM1658138_nochipID8.C20" 
[269] "GSM1658139_nochipID8.C22"  "GSM1658140_nochipID8.C23"  "GSM1658141_nochipID8.C25"  "GSM1658142_nochipID8.C28" 
[273] "GSM1658143_nochipID8.C29"  "GSM1658144_nochipID8.C30"  "GSM1658145_nochipID8.C32"  "GSM1658146_nochipID8.C36" 
[277] "GSM1658147_nochipID8.C37"  "GSM1658148_nochipID8.C39"  "GSM1658149_nochipID8.C40"  "GSM1658150_nochipID8.C41" 
[281] "GSM1658151_nochipID8.C42"  "GSM1658152_nochipID8.C43"  "GSM1658153_nochipID8.C45"  "GSM1658154_nochipID8.C48" 
[285] "GSM1658155_nochipID8.C49"  "GSM1658156_nochipID8.C50"  "GSM1658157_nochipID8.C52"  "GSM1658158_nochipID8.C53" 
[289] "GSM1658159_nochipID8.C54"  "GSM1658160_nochipID8.C55"  "GSM1658161_nochipID8.C56"  "GSM1658162_nochipID8.C57" 
[293] "GSM1658163_nochipID8.C60"  "GSM1658164_nochipID8.C61"  "GSM1658165_nochipID8.C64"  "GSM1658166_nochipID8.C65" 
[297] "GSM1658167_nochipID8.C66"  "GSM1658168_nochipID8.C67"  "GSM1658169_nochipID8.C70"  "GSM1658170_nochipID8.C75" 
[301] "GSM1658171_nochipID8.C77"  "GSM1658172_nochipID8.C78"  "GSM1658173_nochipID8.C79"  "GSM1658174_nochipID8.C81" 
[305] "GSM1658175_nochipID8.C82"  "GSM1658176_nochipID8.C84"  "GSM1658177_nochipID8.C85"  "GSM1658178_nochipID8.C87" 
[309] "GSM1658179_nochipID8.C88"  "GSM1658180_nochipID8.C90"  "GSM1658181_nochipID8.C92"  "GSM1658182_nochipID8.C95" 
[313] "GSM1658183_nochipID8.C96"  "GSM1658184_nochipID9.C01"  "GSM1658185_nochipID9.C02"  "GSM1658186_nochipID9.C04" 
[317] "GSM1658187_nochipID9.C09"  "GSM1658188_nochipID9.C14"  "GSM1658189_nochipID9.C18"  "GSM1658190_nochipID9.C26" 
[321] "GSM1658191_nochipID9.C37"  "GSM1658192_nochipID9.C42"  "GSM1658193_nochipID9.C57"  "GSM1658194_nochipID9.C59" 
[325] "GSM1658195_nochipID9.C62"  "GSM1658196_nochipID9.C65"  "GSM1658197_nochipID9.C74"  "GSM1658198_nochipID9.C75" 
[329] "GSM1658199_nochipID9.C84"  "GSM1658200_nochipID9.C85"  "GSM1658201_nochipID9.C87"  "GSM1658202_nochipID9.C92" 
[333] "GSM1658203_nochipID10.C02" "GSM1658204_nochipID10.C03" "GSM1658205_nochipID10.C05" "GSM1658206_nochipID10.C07"
[337] "GSM1658207_nochipID10.C11" "GSM1658208_nochipID10.C16" "GSM1658209_nochipID10.C17" "GSM1658210_nochipID10.C19"
[341] "GSM1658211_nochipID10.C25" "GSM1658212_nochipID10.C26" "GSM1658213_nochipID10.C37" "GSM1658214_nochipID10.C39"
[345] "GSM1658215_nochipID10.C42" "GSM1658216_nochipID10.C44" "GSM1658217_nochipID10.C47" "GSM1658218_nochipID10.C49"
[349] "GSM1658219_nochipID10.C50" "GSM1658220_nochipID10.C53" "GSM1658221_nochipID10.C58" "GSM1658222_nochipID10.C65"
[353] "GSM1658223_nochipID10.C74" "GSM1658224_nochipID10.C75" "GSM1658225_nochipID10.C85" "GSM1658226_nochipID10.C88"
[357] "GSM1658227_nochipID10.C93" "GSM1658228_nochipID10.C94" "GSM1658229_nochipID11.C02" "GSM1658230_nochipID11.C03"
[361] "GSM1658231_nochipID11.C06" "GSM1658232_nochipID11.C07" "GSM1658233_nochipID11.C08" "GSM1658234_nochipID11.C10"
[365] "GSM1658235_nochipID11.C15" "GSM1658236_nochipID11.C17" "GSM1658237_nochipID11.C19" "GSM1658238_nochipID11.C20"
[369] "GSM1658239_nochipID11.C21" "GSM1658240_nochipID11.C22" "GSM1658241_nochipID11.C23" "GSM1658242_nochipID11.C25"
[373] "GSM1658243_nochipID11.C30" "GSM1658244_nochipID11.C37" "GSM1658245_nochipID11.C48" "GSM1658246_nochipID11.C49"
[377] "GSM1658247_nochipID11.C50" "GSM1658248_nochipID11.C53" "GSM1658249_nochipID11.C54" "GSM1658251_nochipID11.C55"
[381] "GSM1658253_nochipID11.C56" "GSM1658255_nochipID11.C57" "GSM1658257_nochipID11.C58" "GSM1658259_nochipID11.C59"
[385] "GSM1658262_nochipID11.C60" "GSM1658264_nochipID11.C61" "GSM1658266_nochipID11.C62" "GSM1658268_nochipID11.C63"
[389] "GSM1658270_nochipID11.C64" "GSM1658272_nochipID11.C66" "GSM1658275_nochipID11.C68" "GSM1658277_nochipID11.C69"
[393] "GSM1658279_nochipID11.C75" "GSM1658281_nochipID11.C76" "GSM1658284_nochipID11.C77" "GSM1658286_nochipID11.C78"
[397] "GSM1658288_nochipID11.C79" "GSM1658290_nochipID11.C81" "GSM1658292_nochipID11.C82" "GSM1658294_nochipID11.C83"
[401] "GSM1658297_nochipID11.C84" "GSM1658299_nochipID11.C86" "GSM1658301_nochipID11.C91" "GSM1658304_nochipID11.C93"
[405] "GSM1658305_nochipID13.C07" "GSM1658306_nochipID13.C11" "GSM1658307_nochipID13.C12" "GSM1658308_nochipID13.C14"
[409] "GSM1658309_nochipID13.C15" "GSM1658310_nochipID13.C17" "GSM1658311_nochipID13.C21" "GSM1658312_nochipID13.C25"
[413] "GSM1658313_nochipID13.C28" "GSM1658314_nochipID13.C32" "GSM1658315_nochipID13.C36" "GSM1658316_nochipID13.C45"
[417] "GSM1658317_nochipID13.C46" "GSM1658318_nochipID13.C48" "GSM1658319_nochipID13.C50" "GSM1658320_nochipID13.C55"
[421] "GSM1658321_nochipID13.C57" "GSM1658322_nochipID13.C58" "GSM1658323_nochipID13.C59" "GSM1658324_nochipID13.C61"
[425] "GSM1658325_nochipID13.C63" "GSM1658326_nochipID13.C64" "GSM1658327_nochipID13.C66" "GSM1658328_nochipID13.C67"
[429] "GSM1658329_nochipID13.C68" "GSM1658330_nochipID13.C72" "GSM1658331_nochipID13.C73" "GSM1658332_nochipID13.C74"
[433] "GSM1658333_nochipID13.C75" "GSM1658334_nochipID13.C80" "GSM1658335_nochipID13.C84" "GSM1658336_nochipID13.C87"
[437] "GSM1658337_nochipID13.C93" "GSM1658338_nochipID4.C03"  "GSM1658339_nochipID4.C04"  "GSM1658340_nochipID4.C10" 
[441] "GSM1658341_nochipID4.C14"  "GSM1658342_nochipID4.C18"  "GSM1658343_nochipID4.C19"  "GSM1658344_nochipID4.C20" 
[445] "GSM1658345_nochipID4.C21"  "GSM1658346_nochipID4.C33"  "GSM1658347_nochipID4.C34"  "GSM1658348_nochipID4.C38" 
[449] "GSM1658349_nochipID4.C39"  "GSM1658350_nochipID4.C41"  "GSM1658351_nochipID4.C42"  "GSM1658352_nochipID4.C44" 
[453] "GSM1658353_nochipID4.C49"  "GSM1658354_nochipID4.C52"  "GSM1658355_nochipID4.C53"  "GSM1658356_nochipID4.C59" 
[457] "GSM1658357_nochipID4.C62"  "GSM1658358_nochipID4.C63"  "GSM1658359_nochipID4.C66"  "GSM1658360_nochipID4.C74" 
[461] "GSM1658361_nochipID4.C77"  "GSM1658362_nochipID4.C78"  "GSM1658363_nochipID4.C84"  "GSM1658364_nochipID4.C89" 
[465] "GSM1658365_nochipID4.C95"  "GSM1658366_nochipID4.C96" 

all input files has same first column, which acts as index. rename 2nd column’s header to match source filename remove redundant first column then, append to bigger dataframe horizontally (by column) end result is a single dataframe containing all concatenated data from multiple csv files

#df<-read.csv("../../../gseCSV/GSM1657871_1772078217.C03.csv", header = FALSE, stringsAsFactors = FALSE, sep = "\t") #use relative path
inGSE_df<-data.frame(nrow=22088) #initialize empty 22088x0 dataframe for receiving input files
#inputFileNameList<-c("../../../gseCSV/GSM1657872_1772078217.C04.csv","../../../gseCSV/GSM1657873_1772078217.C06.csv","../../../gseCSV/GSM1657874_1772078217.C07.csv") #list of input files with full path name and extension 
#inputFileNameList<-c("GSM1657871_1772078217.C03","GSM1657872_1772078217.C04","GSM1657873_1772078217.C06","GSM1657874_1772078217.C07") #list of input files, but without full path name and extension
first=1 #set first inout dataframe flag to TRUE
inputFileNameList<-inputFileList #use list of file names gained from previous cell

for (f in inputFileNameList){
  #fn<-paste("../../../gseCSV/", f,".csv", sep ="") #reconstruct full path and filename
  fn<-paste("../../../gseCSV/", f, sep ="") #reconstruct full relative path and filename with extension already included
  fs<-sub(".csv$", "", f) #remove extension from file name
  fi<-paste(fs,"_Index")
  #print(fn) #displays input filenames
  
  df2<-read.csv(fn, header = FALSE, stringsAsFactors = FALSE, sep = "\t")
  
  names(df2)[1]<- fi #rename first column's header
  names(df2)[2]<- fs #rename second column's header
  
  if (first==0){ #If current input dataframe is not the first in entire dataframe
    df2[1]<-NULL #drop first column, because it's redundant (deactivate this line to perform all-column append to see if all rows align)
  }
  
  inGSE_df<-cbind(inGSE_df,df2) #append new df
  first=0 #no longer the first dataframe, set flag to FALSE
}

inGSE_df[1]<-NULL #drop first column (not used. final cleanup)

print(inGSE_df)

how to read this?? GSE67835-GPL18573_series_matrix.txt GSE67835-GPL15520_series_matrix.txt

mat <- read.table("../../../matrix/GSE67835-GPL18573_series_matrix.txt")#, header = TRUE, sep = "")

Error in scan(file = file, what = what, sep = sep, quote = quote, dec = dec,  : 
  line 36 did not have 2 elements

#0. excluded cells that had less than 400000 reads, # reducing the initial dataset of 482 cells to 466 already done in imported GSE dataset (466 columns excluding index column)

#1. scde: Pairwise distances between cells

scde_df<-inGSE_df

#2. viSNE <- tsne: Dimensionality reduction of the distances #is the source package tsne or Rtsne or cytobankAPI???

##Rtsne method: #remove missing data #make sure unique row ID exists

##cytobankAPI method: #cytobankAPI needs username and password for aunthethication to site??? #viSNE is a Premium Cytobank feature

#endpoint.method -> viSNE , dimensionality_reduction

#copied from https://rdrr.io/cran/CytobankAPI/f/vignettes/cytobank-quickstart.Rmd section: “Making a request”

#Requests to Cytobank API endpoints can only be made after authenticating (see above). #The authentication object will be passed as the first parameter of any endpoint request.

Making a request to the ‘experiments’ endpoint to create a new experiment

#new_experiment <- experiments.new(cyto_session, experiment_name=“My New Experiment”, purpose=“CytobankAPI quickstart vignette”) # #View(new_experiment) # #c1 <- c(1, 0.007, 0, 0.0023, 0, 0.0026) # #new_experiment_dataframe <- data.frame(id=c(1), # version=c(42), # purpose=c(“CytobankAPI quickstart vignette”), # comments=c(““), # public=c(FALSE), # deleted=c(FALSE), # sources=c(”“), # experimentName=c(”My New Experiment”), # …=c(“…”), # stringsAsFactors=FALSE) # #knitr::kable(new_experiment_dataframe)

#Generating viSNE maps: (see Supplementary Table 2) # 2a. uniformly subsample between 6,000 and 12,000 cells

2b. ViSNE (500 iterations) -> project data to 2D

All runs used:

1. an identical random seed

2. default t-SNE parameters:

1. perplexity = 30

2. momentum = …

a. 0.5 for initial 250 iterations

b. 0.8 for remaining (250) iterations

3. epsilon = 500

4. lie factor = …

a. 4 for initial 100 iterations

b. 1 for remaining (400) iterations

2c. cyt: visualize viSNE maps and figures

(color coding by subtype, by marker expression levels and in plotting expression level densities).

non-existent???

#3. mclust: Subsequent clustering # w/ Bayesian information criterion (BIC) for parameterized Gaussian mixture models fitted by EM algorithm initialized by model-based hierarchical clustering

#4. igraph: Minimum spanning trees, community identification and computation of longest paths

#5. FactoMineR: Principal components analysis (PCA)